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Finding metastable states in real-world time series with recurrence networks
I Vega, C Schütte, TOF Conrad - Physica A: Statistical Mechanics and its …, 2016 - Elsevier
In the framework of time series analysis with recurrence networks, we introduce a self-
adaptive method that determines the elusive recurrence threshold and identifies metastable …
adaptive method that determines the elusive recurrence threshold and identifies metastable …
Modularity in Biological Networks
S Hüffner - 2015 - refubium.fu-berlin.de
Netzwerke werden häufig benutzt, um komplexe reale Netzwerke wie die Zelle oder das
Gehirn zu modellieren. Ein wichtiger Begriff zur Analyse von Netzwerken ist Modularität …
Gehirn zu modellieren. Ein wichtiger Begriff zur Analyse von Netzwerken ist Modularität …
Reconstruction and analysis of the state space for the identification of dynamical states in real-world time series
ID Vega del Valle - 2017 - refubium.fu-berlin.de
One of the main goals of analyzing a high-dimensional time series is to identify structures in
it. Some of these structures correspond to important dynamical features in the underlying …
it. Some of these structures correspond to important dynamical features in the underlying …
Reconstruction and analysis of the state space for the identification of dynamical states in real-world time series
V del Valle, I Donaji - 2017 - pure.mpg.de
One of the main goals of analyzing a high-dimensional time series is to identify structures in
it. Some of these structures correspond to important dynamical features in the underlying …
it. Some of these structures correspond to important dynamical features in the underlying …
SAIMeR: Self-adapted method for the identification of metastable states in real-world time series
In the framework of time series analysis with recurrence networks, we introduce SAIMeR, a
heuristic self-adapted method that determines the elusive recurrence threshold and …
heuristic self-adapted method that determines the elusive recurrence threshold and …